{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 第七章 组合学习"
   ]
  },
  {
   "attachments": {
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     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](picture/多数票机制的集成学习.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "0.03432750701904297"
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from scipy.special import comb  # 计算排列组合\n",
    "import math\n",
    "\n",
    "\n",
    "def ensemble_error(n_classifier, error):  # 计算多个分类器的错误\n",
    "    k_start = int(math.ceil(n_classifier / 2.))\n",
    "    probs = [comb(n_classifier, k) * error**k * (1-error)**(n_classifier - k)\n",
    "             for k in range(k_start, n_classifier + 1)]\n",
    "    return sum(probs)\n",
    "\n",
    "\n",
    "ensemble_error(n_classifier=11, error=0.25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "error_range = np.arange(0.0, 1.01, 0.01)\n",
    "ens_errors = [ensemble_error(n_classifier=11, error=error)\n",
    "              for error in error_range]#计算不同的组合模型的错误判断率\n",
    "plt.plot(error_range,\n",
    "         ens_errors,\n",
    "         label='Ensemble error',\n",
    "         linewidth=2)\n",
    "\n",
    "plt.plot(error_range,\n",
    "         error_range,\n",
    "         linestyle='--',\n",
    "         label='Base error',\n",
    "         linewidth=2)\n",
    "\n",
    "plt.xlabel('Base error')\n",
    "plt.ylabel('Base/Ensemble error')\n",
    "plt.legend(loc='upper left')\n",
    "plt.grid(alpha=0.5)\n",
    "#plt.savefig('images/07_03.png', dpi=300)\n",
    "plt.show()\n",
    "#所有的都小于0.5的时候，组合模型是一定小一点的 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "0"
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#加权多数票机制，每种分类器的权重不一样,虽然只有第三个分类器认为应该预测为1，但是其权重最大0.6，所以最终的预测结果还是1\n",
    "np.argmax(np.bincount([0,0,1],weights=[0.2,0.2,0.6]))\n",
    "\n",
    "#基于概率也可以使用\n",
    "ex=np.array([[0.9,0.1],\n",
    "           [0.8,0.2],\n",
    "           [0.6,0.4]])\n",
    "p=np.average(ex,axis=0,weights=[0.2,0.2,0.6])\n",
    "np.argmax(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#实现组合分类器\n",
    "from sklearn.base import BaseEstimator,ClassifierMixin,clone\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "import six#保证分类器的版本相兼容\n",
    "from sklearn.pipeline import _name_estimators\n",
    "import operator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "class MajorityVoteClassifier(BaseEstimator,\n",
    "                             ClassifierMixin):\n",
    "    \"\"\" A majority vote ensemble classifier\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    classifiers : array-like, shape = [n_classifiers]\n",
    "      Different classifiers for the ensemble\n",
    "\n",
    "    vote : str, {'classlabel', 'probability'} (default='label')\n",
    "      If 'classlabel' the prediction is based on the argmax of\n",
    "        class labels. Else if 'probability', the argmax of\n",
    "        the sum of probabilities is used to predict the class label\n",
    "        (recommended for calibrated classifiers).\n",
    "\n",
    "    weights : array-like, shape = [n_classifiers], optional (default=None)\n",
    "      If a list of `int` or `float` values are provided, the classifiers\n",
    "      are weighted by importance; Uses uniform weights if `weights=None`.\n",
    "\n",
    "    \"\"\"\n",
    "\n",
    "    def __init__(self, classifiers, vote='classlabel', weights=None):\n",
    "\n",
    "        self.classifiers = classifiers\n",
    "        self.named_classifiers = {key: value for key, value\n",
    "                                  in _name_estimators(classifiers)}\n",
    "        self.vote = vote\n",
    "        self.weights = weights\n",
    "\n",
    "    def fit(self, X, y):\n",
    "        \"\"\" Fit classifiers.\n",
    "\n",
    "        Parameters\n",
    "        ----------\n",
    "        X : {array-like, sparse matrix}, shape = [n_samples, n_features]\n",
    "            Matrix of training samples.\n",
    "\n",
    "        y : array-like, shape = [n_samples]\n",
    "            Vector of target class labels.\n",
    "\n",
    "        Returns\n",
    "        -------\n",
    "        self : object\n",
    "\n",
    "        \"\"\"\n",
    "        if self.vote not in ('probability', 'classlabel'):\n",
    "            raise ValueError(\"vote must be 'probability' or 'classlabel'\"\n",
    "                             \"; got (vote=%r)\"\n",
    "                             % self.vote)\n",
    "\n",
    "        if self.weights and len(self.weights) != len(self.classifiers):\n",
    "            raise ValueError('Number of classifiers and weights must be equal'\n",
    "                             '; got %d weights, %d classifiers'\n",
    "                             % (len(self.weights), len(self.classifiers)))\n",
    "\n",
    "        # Use LabelEncoder to ensure class labels start with 0, which\n",
    "        # is important for np.argmax call in self.predict\n",
    "        self.lablenc_ = LabelEncoder()\n",
    "        self.lablenc_.fit(y)\n",
    "        self.classes_ = self.lablenc_.classes_\n",
    "        self.classifiers_ = []\n",
    "        for clf in self.classifiers:\n",
    "            fitted_clf = clone(clf).fit(X, self.lablenc_.transform(y))\n",
    "            self.classifiers_.append(fitted_clf)\n",
    "        return self\n",
    "\n",
    "    def predict(self, X):\n",
    "        \"\"\" Predict class labels for X.\n",
    "\n",
    "        Parameters\n",
    "        ----------\n",
    "        X : {array-like, sparse matrix}, shape = [n_samples, n_features]\n",
    "            Matrix of training samples.\n",
    "\n",
    "        Returns\n",
    "        ----------\n",
    "        maj_vote : array-like, shape = [n_samples]\n",
    "            Predicted class labels.\n",
    "\n",
    "        \"\"\"\n",
    "        if self.vote == 'probability':\n",
    "            maj_vote = np.argmax(self.predict_proba(X), axis=1)\n",
    "        else:  # 'classlabel' vote\n",
    "\n",
    "            #  Collect results from clf.predict calls\n",
    "            predictions = np.asarray([clf.predict(X)\n",
    "                                      for clf in self.classifiers_]).T\n",
    "\n",
    "            maj_vote = np.apply_along_axis(\n",
    "                lambda x:\n",
    "                np.argmax(np.bincount(x,\n",
    "                                      weights=self.weights)),\n",
    "                axis=1,\n",
    "                arr=predictions)\n",
    "        maj_vote = self.lablenc_.inverse_transform(maj_vote)\n",
    "        return maj_vote\n",
    "\n",
    "    def predict_proba(self, X):\n",
    "        \"\"\" Predict class probabilities for X.\n",
    "\n",
    "        Parameters\n",
    "        ----------\n",
    "        X : {array-like, sparse matrix}, shape = [n_samples, n_features]\n",
    "            Training vectors, where n_samples is the number of samples and\n",
    "            n_features is the number of features.\n",
    "\n",
    "        Returns\n",
    "        ----------\n",
    "        avg_proba : array-like, shape = [n_samples, n_classes]\n",
    "            Weighted average probability for each class per sample.\n",
    "\n",
    "        \"\"\"\n",
    "        probas = np.asarray([clf.predict_proba(X)\n",
    "                             for clf in self.classifiers_])\n",
    "        avg_proba = np.average(probas, axis=0, weights=self.weights)\n",
    "        return avg_proba\n",
    "\n",
    "    def get_params(self, deep=True):#输出分类器的参数\n",
    "        \"\"\" Get classifier parameter names for GridSearch\"\"\"\n",
    "        if not deep:\n",
    "            return super(MajorityVoteClassifier, self).get_params(deep=False)\n",
    "        else:\n",
    "            out = self.named_classifiers.copy()\n",
    "            for name, step in six.iteritems(self.named_classifiers):\n",
    "                for key, value in six.iteritems(step.get_params(deep=True)):\n",
    "                    out['%s__%s' % (name, key)] = value\n",
    "            return out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10-fold cross validation:\n",
      "\n",
      "ROC AUC: 0.92 (+/- 0.15) [Logistic regression]\n",
      "ROC AUC: 0.87 (+/- 0.18) [Decision tree]\n",
      "ROC AUC: 0.85 (+/- 0.13) [KNN]\n"
     ]
    }
   ],
   "source": [
    "from sklearn import datasets\n",
    "from sklearn.model_selection import train_test_split, cross_val_score\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "iris = datasets.load_iris()\n",
    "X, y = iris.data[50:, [1, 2]], iris.target[50:]\n",
    "le = LabelEncoder()\n",
    "y = le.fit_transform(y)\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y,\n",
    "                                                    test_size=0.5,\n",
    "                                                    random_state=1,\n",
    "                                                    stratify=y)\n",
    "\n",
    "clf1 = LogisticRegression(penalty='l2',\n",
    "                          C=0.001,\n",
    "                          random_state=1)\n",
    "\n",
    "clf2 = DecisionTreeClassifier(max_depth=1,\n",
    "                              criterion='entropy',\n",
    "                              random_state=0)\n",
    "\n",
    "clf3 = KNeighborsClassifier(n_neighbors=1,\n",
    "                            p=2,\n",
    "                            metric='minkowski')\n",
    "\n",
    "pipe1 = Pipeline([['sc', StandardScaler()],\n",
    "                  ['clf', clf1]])\n",
    "pipe3 = Pipeline([['sc', StandardScaler()],\n",
    "                  ['clf', clf3]])\n",
    "\n",
    "clf_labels = ['Logistic regression', 'Decision tree', 'KNN']\n",
    "\n",
    "print('10-fold cross validation:\\n')\n",
    "for clf, label in zip([pipe1, clf2, pipe3], clf_labels):\n",
    "    scores = cross_val_score(estimator=clf,\n",
    "                             X=X_train,\n",
    "                             y=y_train,\n",
    "                             cv=10,\n",
    "                             scoring='roc_auc')\n",
    "    print(\"ROC AUC: %0.2f (+/- %0.2f) [%s]\"\n",
    "          % (scores.mean(), scores.std(), label))\n",
    "#三种分类器的准确率差不多"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ROC AUC: 0.92 (+/- 0.15) [Logistic regression]\n",
      "ROC AUC: 0.87 (+/- 0.18) [Decision tree]\n",
      "ROC AUC: 0.85 (+/- 0.13) [KNN]\n",
      "ROC AUC: 0.98 (+/- 0.05) [Majority voting]\n"
     ]
    }
   ],
   "source": [
    "#使用组合模型\n",
    "mv_clf=MajorityVoteClassifier(classifiers=[pipe1,clf2,pipe3])#将三种分类器传入\n",
    "clf_labels+=['Majority voting']\n",
    "all_clf=[pipe1,clf2,pipe3,mv_clf]\n",
    "for clf, label in zip(all_clf, clf_labels):\n",
    "    scores = cross_val_score(estimator=clf,\n",
    "                             X=X_train,\n",
    "                             y=y_train,\n",
    "                             cv=10,\n",
    "                             scoring='roc_auc')\n",
    "    print(\"ROC AUC: %0.2f (+/- %0.2f) [%s]\"\n",
    "          % (scores.mean(), scores.std(), label))\n",
    "#显然集合模型的效果更好"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 864x720 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 绘制roc曲线\n",
    "from sklearn.metrics import roc_curve\n",
    "from sklearn.metrics import auc\n",
    "colors = ['black', 'orange', 'blue', 'green']\n",
    "linestyles = [':', '--', '-.', '-']\n",
    "plt.figure(figsize=(12, 10))\n",
    "for clf, label, clr, ls in zip(all_clf,\n",
    "                               clf_labels, colors, linestyles):\n",
    "\n",
    "    # assuming the label of the positive class is 1\n",
    "    y_pred = clf.fit(X_train,\n",
    "                     y_train).predict_proba(X_test)[:, 1]\n",
    "    fpr, tpr, thresholds = roc_curve(y_true=y_test,\n",
    "                                     y_score=y_pred)\n",
    "    roc_auc = auc(x=fpr, y=tpr)\n",
    "    plt.plot(fpr, tpr,\n",
    "             color=clr,\n",
    "             linestyle=ls,\n",
    "             label='%s (auc = %0.2f)' % (label, roc_auc))\n",
    "\n",
    "plt.legend(loc='lower right')\n",
    "plt.plot([0, 1], [0, 1],\n",
    "         linestyle='--',\n",
    "         color='gray',\n",
    "         linewidth=2)\n",
    "\n",
    "plt.xlim([-0.1, 1.1])\n",
    "plt.ylim([-0.1, 1.1])\n",
    "plt.grid(alpha=0.5)\n",
    "plt.xlabel('False positive rate (FPR)')\n",
    "plt.ylabel('True positive rate (TPR)')\n",
    "\n",
    "\n",
    "#plt.savefig('images/07_04', dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 864x720 with 4 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from itertools import product#生成器\n",
    "sc = StandardScaler()\n",
    "X_train_std = sc.fit_transform(X_train)\n",
    "\n",
    "all_clf = [pipe1, clf2, pipe3, mv_clf]\n",
    "\n",
    "x_min = X_train_std[:, 0].min() - 1\n",
    "x_max = X_train_std[:, 0].max() + 1\n",
    "y_min = X_train_std[:, 1].min() - 1\n",
    "y_max = X_train_std[:, 1].max() + 1\n",
    "\n",
    "xx, yy = np.meshgrid(np.arange(x_min, x_max, 0.1),\n",
    "                     np.arange(y_min, y_max, 0.1))#产生一个x和y的区域，就是两个特征的值的范围,网格数据，并且用这个网格数据去预测\n",
    "\n",
    "f, axarr = plt.subplots(nrows=2, ncols=2,\n",
    "                        sharex='col',\n",
    "                        sharey='row',\n",
    "                        figsize=(12, 10))\n",
    "\n",
    "for idx, clf, tt in zip(product([0, 1], [0, 1]),#所有的组合（0，0），（0，1），（1，0），（1，1）\n",
    "                        all_clf, clf_labels):\n",
    "    clf.fit(X_train_std, y_train)\n",
    "\n",
    "    Z = clf.predict(np.c_[xx.ravel(), yy.ravel()])#把俩个一维的数组转换成一个二维的数据，数组的zip,ravel是将多维数组转换为一位数组，np.c_是组合\n",
    "    Z = Z.reshape(xx.shape)\n",
    "\n",
    "    axarr[idx[0], idx[1]].contourf(xx, yy, Z, alpha=0.3)#每个小图上填充等高线,线上是等高的，线的两边是不同的分类\n",
    "\n",
    "    axarr[idx[0], idx[1]].scatter(X_train_std[y_train == 0, 0],\n",
    "                                  X_train_std[y_train == 0, 1],\n",
    "                                  c='blue',\n",
    "                                  marker='^',\n",
    "                                  s=50)#画出分类为0的散点\n",
    "\n",
    "    axarr[idx[0], idx[1]].scatter(X_train_std[y_train == 1, 0],\n",
    "                                  X_train_std[y_train == 1, 1],\n",
    "                                  c='green',\n",
    "                                  marker='o',\n",
    "                                  s=50)#画出分裂为1的散点\n",
    "\n",
    "    axarr[idx[0], idx[1]].set_title(tt)\n",
    "\n",
    "plt.text(-3.5, -5.,\n",
    "         s='Sepal width [standardized]',\n",
    "         ha='center', va='center', fontsize=12)\n",
    "plt.text(-12.5, 4.5,\n",
    "         s='Petal length [standardized]',\n",
    "         ha='center', va='center',\n",
    "         fontsize=12, rotation=90)\n",
    "\n",
    "#plt.savefig('images/07_05', dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "{'pipeline-1': Pipeline(steps=[('sc', StandardScaler()),\n                 ['clf', LogisticRegression(C=0.001, random_state=1)]]),\n 'decisiontreeclassifier': DecisionTreeClassifier(criterion='entropy', max_depth=1, random_state=0),\n 'pipeline-2': Pipeline(steps=[('sc', StandardScaler()),\n                 ['clf', KNeighborsClassifier(n_neighbors=1)]]),\n 'pipeline-1__memory': None,\n 'pipeline-1__steps': [('sc', StandardScaler()),\n  ['clf', LogisticRegression(C=0.001, random_state=1)]],\n 'pipeline-1__verbose': False,\n 'pipeline-1__sc': StandardScaler(),\n 'pipeline-1__clf': LogisticRegression(C=0.001, random_state=1),\n 'pipeline-1__sc__copy': True,\n 'pipeline-1__sc__with_mean': True,\n 'pipeline-1__sc__with_std': True,\n 'pipeline-1__clf__C': 0.001,\n 'pipeline-1__clf__class_weight': None,\n 'pipeline-1__clf__dual': False,\n 'pipeline-1__clf__fit_intercept': True,\n 'pipeline-1__clf__intercept_scaling': 1,\n 'pipeline-1__clf__l1_ratio': None,\n 'pipeline-1__clf__max_iter': 100,\n 'pipeline-1__clf__multi_class': 'auto',\n 'pipeline-1__clf__n_jobs': None,\n 'pipeline-1__clf__penalty': 'l2',\n 'pipeline-1__clf__random_state': 1,\n 'pipeline-1__clf__solver': 'lbfgs',\n 'pipeline-1__clf__tol': 0.0001,\n 'pipeline-1__clf__verbose': 0,\n 'pipeline-1__clf__warm_start': False,\n 'decisiontreeclassifier__ccp_alpha': 0.0,\n 'decisiontreeclassifier__class_weight': None,\n 'decisiontreeclassifier__criterion': 'entropy',\n 'decisiontreeclassifier__max_depth': 1,\n 'decisiontreeclassifier__max_features': None,\n 'decisiontreeclassifier__max_leaf_nodes': None,\n 'decisiontreeclassifier__min_impurity_decrease': 0.0,\n 'decisiontreeclassifier__min_samples_leaf': 1,\n 'decisiontreeclassifier__min_samples_split': 2,\n 'decisiontreeclassifier__min_weight_fraction_leaf': 0.0,\n 'decisiontreeclassifier__random_state': 0,\n 'decisiontreeclassifier__splitter': 'best',\n 'pipeline-2__memory': None,\n 'pipeline-2__steps': [('sc', StandardScaler()),\n  ['clf', KNeighborsClassifier(n_neighbors=1)]],\n 'pipeline-2__verbose': False,\n 'pipeline-2__sc': StandardScaler(),\n 'pipeline-2__clf': KNeighborsClassifier(n_neighbors=1),\n 'pipeline-2__sc__copy': True,\n 'pipeline-2__sc__with_mean': True,\n 'pipeline-2__sc__with_std': True,\n 'pipeline-2__clf__algorithm': 'auto',\n 'pipeline-2__clf__leaf_size': 30,\n 'pipeline-2__clf__metric': 'minkowski',\n 'pipeline-2__clf__metric_params': None,\n 'pipeline-2__clf__n_jobs': None,\n 'pipeline-2__clf__n_neighbors': 1,\n 'pipeline-2__clf__p': 2,\n 'pipeline-2__clf__weights': 'uniform'}"
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mv_clf.get_params()#查看参数，方便优化每个分类器"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.840+-0.10 {'decisiontreeclassifier__max_depth': 1, 'pipeline-1__clf__C': 0.001}\n",
      "0.860+-0.10 {'decisiontreeclassifier__max_depth': 1, 'pipeline-1__clf__C': 0.1}\n",
      "0.880+-0.10 {'decisiontreeclassifier__max_depth': 1, 'pipeline-1__clf__C': 100}\n",
      "0.840+-0.10 {'decisiontreeclassifier__max_depth': 2, 'pipeline-1__clf__C': 0.001}\n",
      "0.860+-0.10 {'decisiontreeclassifier__max_depth': 2, 'pipeline-1__clf__C': 0.1}\n",
      "0.880+-0.10 {'decisiontreeclassifier__max_depth': 2, 'pipeline-1__clf__C': 100}\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import GridSearchCV#通过网格搜索来优化分类器\n",
    "params={'decisiontreeclassifier__max_depth': [1,2],\n",
    "       'pipeline-1__clf__C': [0.001,0.1,100] }\n",
    "grid=GridSearchCV(estimator=mv_clf,param_grid=params,cv=10)\n",
    "grid.fit(X_train,y_train)\n",
    "for i in range(6):\n",
    "    print('%.3f+-%0.2f %r'%(grid.cv_results_['mean_test_score'][i],grid.cv_results_['std_test_score'][i]/2,grid.cv_results_['params'][i]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best parameters: {'decisiontreeclassifier__max_depth': 1, 'pipeline-1__clf__C': 100}\n",
      "Accuracy: 0.88\n"
     ]
    }
   ],
   "source": [
    "print('Best parameters: %s' % grid.best_params_)\n",
    "print('Accuracy: %.2f' % grid.best_score_)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 套代法集成学习"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "![](picture/套袋集成分类器.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "outputs": [
    {
     "data": {
      "text/plain": "   Class label  Alcohol  Malic acid   Ash  Alcalinity of ash  Magnesium  \\\n0            1    14.23        1.71  2.43               15.6        127   \n1            1    13.20        1.78  2.14               11.2        100   \n2            1    13.16        2.36  2.67               18.6        101   \n3            1    14.37        1.95  2.50               16.8        113   \n4            1    13.24        2.59  2.87               21.0        118   \n\n   Total phenols  Flavanoids  Nonflavanoid phenols  Proanthocyanins  \\\n0           2.80        3.06                  0.28             2.29   \n1           2.65        2.76                  0.26             1.28   \n2           2.80        3.24                  0.30             2.81   \n3           3.85        3.49                  0.24             2.18   \n4           2.80        2.69                  0.39             1.82   \n\n   Color intensity   Hue  OD280/OD315 of diluted wines  Proline  \n0             5.64  1.04                          3.92     1065  \n1             4.38  1.05                          3.40     1050  \n2             5.68  1.03                          3.17     1185  \n3             7.80  0.86                          3.45     1480  \n4             4.32  1.04                          2.93      735  ",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Class label</th>\n      <th>Alcohol</th>\n      <th>Malic acid</th>\n      <th>Ash</th>\n      <th>Alcalinity of ash</th>\n      <th>Magnesium</th>\n      <th>Total phenols</th>\n      <th>Flavanoids</th>\n      <th>Nonflavanoid phenols</th>\n      <th>Proanthocyanins</th>\n      <th>Color intensity</th>\n      <th>Hue</th>\n      <th>OD280/OD315 of diluted wines</th>\n      <th>Proline</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1</td>\n      <td>14.23</td>\n      <td>1.71</td>\n      <td>2.43</td>\n      <td>15.6</td>\n      <td>127</td>\n      <td>2.80</td>\n      <td>3.06</td>\n      <td>0.28</td>\n      <td>2.29</td>\n      <td>5.64</td>\n      <td>1.04</td>\n      <td>3.92</td>\n      <td>1065</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1</td>\n      <td>13.20</td>\n      <td>1.78</td>\n      <td>2.14</td>\n      <td>11.2</td>\n      <td>100</td>\n      <td>2.65</td>\n      <td>2.76</td>\n      <td>0.26</td>\n      <td>1.28</td>\n      <td>4.38</td>\n      <td>1.05</td>\n      <td>3.40</td>\n      <td>1050</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>1</td>\n      <td>13.16</td>\n      <td>2.36</td>\n      <td>2.67</td>\n      <td>18.6</td>\n      <td>101</td>\n      <td>2.80</td>\n      <td>3.24</td>\n      <td>0.30</td>\n      <td>2.81</td>\n      <td>5.68</td>\n      <td>1.03</td>\n      <td>3.17</td>\n      <td>1185</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>1</td>\n      <td>14.37</td>\n      <td>1.95</td>\n      <td>2.50</td>\n      <td>16.8</td>\n      <td>113</td>\n      <td>3.85</td>\n      <td>3.49</td>\n      <td>0.24</td>\n      <td>2.18</td>\n      <td>7.80</td>\n      <td>0.86</td>\n      <td>3.45</td>\n      <td>1480</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>1</td>\n      <td>13.24</td>\n      <td>2.59</td>\n      <td>2.87</td>\n      <td>21.0</td>\n      <td>118</td>\n      <td>2.80</td>\n      <td>2.69</td>\n      <td>0.39</td>\n      <td>1.82</td>\n      <td>4.32</td>\n      <td>1.04</td>\n      <td>2.93</td>\n      <td>735</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#应用套袋技术对葡萄酒的数据集中的样本进行分类\n",
    "import pandas as pd\n",
    "df_wine = pd.read_csv('https://archive.ics.uci.edu/ml/'\n",
    "                 'machine-learning-databases'\n",
    "                 '/wine/wine.data', header=None)\n",
    "df_wine.columns = ['Class label', 'Alcohol', 'Malic acid', 'Ash',\n",
    "                   'Alcalinity of ash', 'Magnesium', 'Total phenols',\n",
    "                   'Flavanoids', 'Nonflavanoid phenols', 'Proanthocyanins',\n",
    "                   'Color intensity', 'Hue',\n",
    "                   'OD280/OD315 of diluted wines', 'Proline']\n",
    "\n",
    "df_wine.head()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "outputs": [],
   "source": [
    "df_wine=df_wine[df_wine['Class label']!=1]\n",
    "y=df_wine['Class label'].values\n",
    "X=df_wine[['Alcohol','OD280/OD315 of diluted wines']].values"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "outputs": [],
   "source": [
    "#编码并分割数据\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn.model_selection import train_test_split\n",
    "le=LabelEncoder()\n",
    "y=le.fit_transform(y)\n",
    "X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=0.2,random_state=1,stratify=y)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "outputs": [],
   "source": [
    "#用一颗决策树分类器与500课决策树用套袋法的集成分类器作对比\n",
    "from sklearn.ensemble import BaggingClassifier\n",
    "tree=DecisionTreeClassifier(criterion='entropy',\n",
    "                            random_state=1,\n",
    "                            max_depth=None)\n",
    "bag=BaggingClassifier(base_estimator=tree,\n",
    "                      n_estimators=500,\n",
    "                      max_samples=1.0,#浮点数和整数会有区别，整数是样本个数，浮点数是样本比例\n",
    "                      max_features=1.0,\n",
    "                      bootstrap=True,\n",
    "                      bootstrap_features=False,\n",
    "                      n_jobs=1,\n",
    "                      random_state=1)\n"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Decision tree train/test accuracies 1.000/0.833\n",
      "Bagging train/test accuracies 1.000/0.917\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import accuracy_score\n",
    "tree = tree.fit(X_train, y_train)\n",
    "y_train_pred = tree.predict(X_train)\n",
    "y_test_pred = tree.predict(X_test)\n",
    "\n",
    "tree_train = accuracy_score(y_train, y_train_pred)\n",
    "tree_test = accuracy_score(y_test, y_test_pred)\n",
    "print('Decision tree train/test accuracies %.3f/%.3f'\n",
    "      % (tree_train, tree_test))\n",
    "\n",
    "bag = bag.fit(X_train, y_train)\n",
    "y_train_pred = bag.predict(X_train)\n",
    "y_test_pred = bag.predict(X_test)\n",
    "\n",
    "bag_train = accuracy_score(y_train, y_train_pred)\n",
    "bag_test = accuracy_score(y_test, y_test_pred)\n",
    "print('Bagging train/test accuracies %.3f/%.3f'\n",
    "      % (bag_train, bag_test))"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 576x216 with 2 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_min = X_train[:, 0].min() - 1\n",
    "x_max = X_train[:, 0].max() + 1\n",
    "y_min = X_train[:, 1].min() - 1\n",
    "y_max = X_train[:, 1].max() + 1\n",
    "\n",
    "xx, yy = np.meshgrid(np.arange(x_min, x_max, 0.1),\n",
    "                     np.arange(y_min, y_max, 0.1))\n",
    "\n",
    "f, axarr = plt.subplots(nrows=1, ncols=2,\n",
    "                        sharex='col',\n",
    "                        sharey='row',\n",
    "                        figsize=(8, 3))\n",
    "\n",
    "\n",
    "for idx, clf, tt in zip([0, 1],\n",
    "                        [tree, bag],\n",
    "                        ['Decision tree', 'Bagging']):\n",
    "    clf.fit(X_train, y_train)\n",
    "\n",
    "    Z = clf.predict(np.c_[xx.ravel(), yy.ravel()])\n",
    "    Z = Z.reshape(xx.shape)\n",
    "\n",
    "    axarr[idx].contourf(xx, yy, Z, alpha=0.3)\n",
    "    axarr[idx].scatter(X_train[y_train == 0, 0],\n",
    "                       X_train[y_train == 0, 1],\n",
    "                       c='blue', marker='^')\n",
    "\n",
    "    axarr[idx].scatter(X_train[y_train == 1, 0],\n",
    "                       X_train[y_train == 1, 1],\n",
    "                       c='green', marker='o')\n",
    "\n",
    "    axarr[idx].set_title(tt)\n",
    "\n",
    "axarr[0].set_ylabel('Alcohol', fontsize=12)\n",
    "plt.text(10.2, -0.5,\n",
    "         s='OD280/OD315 of diluted wines',\n",
    "         ha='center', va='center', fontsize=12)\n",
    "\n",
    "plt.tight_layout()\n",
    "#plt.savefig('images/07_08.png', dpi=300, bbox_inches='tight')\n",
    "plt.show()\n",
    "#在套袋中更平滑"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "### 通过自适应增加来利用弱学习者"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "![](picture/自适应增强算法.png)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Decision tree train/test accuracies 0.916/0.875\n",
      "Adaboost train/test accuracies 1.000/0.917\n"
     ]
    }
   ],
   "source": [
    "#使用sklearn实现自适应增强\n",
    "from sklearn.ensemble import AdaBoostClassifier\n",
    "tree=DecisionTreeClassifier(criterion=\"entropy\",random_state=1,max_depth=1)\n",
    "ada=AdaBoostClassifier(base_estimator=tree,n_estimators=500,learning_rate=0.1,random_state=1)\n",
    "tree=tree.fit(X_train,y_train)\n",
    "y_train_pred = tree.predict(X_train)\n",
    "y_test_pred = tree.predict(X_test)\n",
    "\n",
    "tree_train = accuracy_score(y_train, y_train_pred)\n",
    "tree_test = accuracy_score(y_test, y_test_pred)\n",
    "print('Decision tree train/test accuracies %.3f/%.3f'\n",
    "      % (tree_train, tree_test))\n",
    "ada=ada.fit(X_train,y_train)\n",
    "y_train_pred = ada.predict(X_train)\n",
    "y_test_pred = ada.predict(X_test)\n",
    "\n",
    "ada_train = accuracy_score(y_train, y_train_pred)\n",
    "ada_test = accuracy_score(y_test, y_test_pred)\n",
    "print('Adaboost train/test accuracies %.3f/%.3f'\n",
    "      % (ada_train, ada_test))"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 720x288 with 2 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
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     "output_type": "display_data"
    }
   ],
   "source": [
    "x_min = X_train[:, 0].min() - 1\n",
    "x_max = X_train[:, 0].max() + 1\n",
    "y_min = X_train[:, 1].min() - 1\n",
    "y_max = X_train[:, 1].max() + 1\n",
    "\n",
    "xx, yy = np.meshgrid(np.arange(x_min, x_max, 0.1),\n",
    "                     np.arange(y_min, y_max, 0.1))\n",
    "\n",
    "f, axarr = plt.subplots(nrows=1, ncols=2,\n",
    "                        sharex='col',\n",
    "                        sharey='row',\n",
    "                        figsize=(10, 4))\n",
    "\n",
    "\n",
    "for idx, clf, tt in zip([0, 1],\n",
    "                        [tree, ada],\n",
    "                        ['Decision tree', 'Adaboost']):\n",
    "    clf.fit(X_train, y_train)\n",
    "\n",
    "    Z = clf.predict(np.c_[xx.ravel(), yy.ravel()])\n",
    "    Z = Z.reshape(xx.shape)\n",
    "\n",
    "    axarr[idx].contourf(xx, yy, Z, alpha=0.3)\n",
    "    axarr[idx].scatter(X_train[y_train == 0, 0],\n",
    "                       X_train[y_train == 0, 1],\n",
    "                       c='blue', marker='^')\n",
    "\n",
    "    axarr[idx].scatter(X_train[y_train == 1, 0],\n",
    "                       X_train[y_train == 1, 1],\n",
    "                       c='green', marker='o')\n",
    "\n",
    "    axarr[idx].set_title(tt)\n",
    "\n",
    "axarr[0].set_ylabel('Alcohol', fontsize=12)\n",
    "plt.text(10.2, -0.5,\n",
    "         s='OD280/OD315 of diluted wines',\n",
    "         ha='center', va='center', fontsize=12)\n",
    "\n",
    "plt.tight_layout()\n",
    "#plt.savefig('images/07_08.png', dpi=300, bbox_inches='tight')\n",
    "plt.show()\n",
    "#Adaboost在决策边界更复杂，预测更准确"
   ],
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   "cell_type": "markdown",
   "source": [
    "### 本章研究了一些最常见和广泛使用的集成学习技术。集成方法组合不同的分类模型来消除各自的弱点，这往往能带来稳定和性能良好的模型，对于工业应用和机器学习竞赛非常有吸引力。本章的开始部分用Python实现了MajorityVoteClassifier，它允许组合不同的分类算法。然后研究了套袋技术，这是一种可以减少模型方差的有用技术，该方法从训练集随机提取引导样本，通过多数票机制把个别训练的分类器组合起来。最后学习了AdaBoost算法，它是一种基于弱学习者从分类错误中学习的算法"
   ],
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   "execution_count": null,
   "outputs": [],
   "source": [],
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     "name": "#%%\n"
    }
   }
  }
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